This document outlines instructions for using simple linear regression to examine the relationship between blood lead values and finger-wrist tapping test scores, including stating the null hypothesis, interpreting the R-Square value, reporting the unstandardized regression coefficient and p-value, writing the estimated equation, calculating a predicted score, and interpreting the slope at an alpha level of 0.05.

1. Model Summary a. Predictors: (Constant), BLOOD LEAD VALUES (MICROGRAMS/100ML)
ANnI/ aN a. Dependent Variable: FINGER-WRIST TAPPING TEST SCORE RIGHT HAND b.
Predictors: (Constant), BLOOD LEAD VALUES (MICROGRAMS/100ML) Coefficients aUse simple
linear regression to examine the effect of blood lead values (SPSS variable name: Id73) on
neurological problems as measured by the finger-wrist tapping test (fwt_r), assuming that finger-
wrist tapping scores are approximately normally distributed (8 points). a. State the null hypothesis
( 1 point). b. Please interpret the R Square value. Include both the independent and dependent
variable in your response. ( 1 point). c. What is the unstandardized regression coefficient and
associated p-value for the independent variable ( 2 points)? d. Write the estimated equation for
this analysis with the y-intercept, regression slope and the variables (2 points). e. Using the
formula in the previous question, if an individual's blood lead level is 85 what is the predicted
finger-wrist tapping score? (1 point) f. Assuming an alpha level of 0.05 , how would you interpret
the slope estimate and its statistical significance? (1 point)?